pca as an optimization problem
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For some reasons, I would like to compute PCA (or, rather the eigenvectors and eigenvalues of a (de-meaned) sample covariance matrix ) using an oprimization function. I think I understood how to set up the objective functions and constraints, but struggling to actually implement it with Matlab. I am referring the first answer: What is the objective function of PCA? .
Could anyone help me to understand how to set up the problem with Matlab?
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Image Analyst
il 14 Ott 2018
Why not just use the built-in pca() function, if you have the Statistics and Machine Learning Toolbox? See attached demos.
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Prabakaran G
il 16 Ago 2022
As per my understanding, PCA can used to reduce the number of input predictors, which make the problem is simpler and generalize. Also, it reduce the complexity of the function to optimize.
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